Why do so many more people do research in Malawi than in Haiti?

Eric Chyn passes along this Marginal Revolution post in which Tyler Cowen asks “to what extent is the choice of venue for study due to what I will call ‘social science infrastructure’?” By “social science infrastructure” Cowen means having a pool of experienced field workers, plus a population that is accustomed to being studied and other less-tangible factors:

I don’t mean roads and bridges. I mean having trained armies of local assistants, data gathering and processing facilities, populations which are used to signing informed consent forms, medical clinics which understand how to work with social scientists and register data, and other less visible assets.

This list hits on some important factors, but it is missing at least of key items:

Existing data, in large quantities and available to the public. I have a colleague who works mostly with secondary data and was born and raised in Haiti but doesn’t do research on the country because there’s nothing to work with. Less data means fewer existing papers, a smaller existing literature available for informing your research (and selling it as publication-worthy!), and it makes running power calculations harder. Running an experiment on a population that has never been studied is an exercise in wasting your time and money.

Experience in the country, both on an individual basis and on the part of one’s colleagues and advisor. It’s much easier to do research in a place where you know the language, have friends, understand aspects of the culture, can get around, and so forth. A very close proxy for having these things personally is knowing some

Ongoing projects to work on. These are a great way to get experience in the country, to pilot survey questions, and even to run mini-experiments. This isn’t only for grad students – faculty tack their questions onto surveys and jump into collaborations as well.

Cowen essentially answers his own question by noting that a large number of field RCTs are set in Western Kenya. Malawi is another development research hotspot, and Northern Uganda seems to be growing as one as well (and I have worked in both). Social science infrastructure is essentially the whole reason why there is so much geographic concentration of development research.

But he missed out on asking the broader question: why are there such huge gaps in social science infrastructure across countries? The answer is suggested by the three components I listed above. What ties them all together is path dependence. At some point fairly long ago, people decided to start doing research in country X. The reasons for this are some mix of the obvious practical issues noted by Cowen (security, language, etc.) and totally idiosyncratic things. This then makes the next set of projects drastically easier: all of a sudden people know someone working in a country, they have a contacts to ask about who to hire as employees, they can pilot their work while interning on another study, and so forth. Then those people have colleagues and students, and the cycle continues.

In the case of Malawi, one of the key early events was the beginning of the MDICP, a longitudinal study of contraceptive use and sexual health behaviors. A tremendous share of the foreign social science researchers that work in Malawi have close connections to that project (including myself – my advisor worked on the 2004 wave, and used it as a platform for her job market experiment). The same goes for the human capital needed to do research – to pick one example, IKI, emerged from the local MDICP research staff.

It’s hard to overstate the strength of the path dependence effect in development research. The difficulty of blazing your own trail is a huge barrier to getting work done. From my perspective, the marginal cost of doing a project in Malawi is a tiny fraction of doing the same thing in Haiti. On the benefit side of the ledger, I’d agree that more people should study Haiti, but economics in particular puts strikingly little weight on the geographic origin of a given dataset. To first order, the economics profession thinks American data is all you need to study anyway; getting people to take any developing-country data seriously can be a challenge, so it’s not surprising that there’s a limited payoff to doing research in a new or under-studied locale.